Automated banking machine processing system and method

ABSTRACT

A system includes a plurality of automated banking machines that each include a card reader and operate to carry out financial transactions. A server computer in operative connection with the plurality of automated banking machines receives processing jobs. The server operates to distribute a plurality of tasks among a plurality of automated banking machines. Each automated banking machine is operative to perform transaction functions such as the dispensing of cash from a cash dispenser.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.10/100,851 filed Mar. 18, 2002. Ser. No. 10/100,851 claims benefit ofU.S. Provisional Application Ser. No. 60/276,974 filed Mar. 19, 2001.The disclosures of each of these applications is incorporated herein byreference.

TECHNICAL FIELD

This invention relates to automated banking machines that operateresponsive to data bearing records such as user cards and which may beclassified in U.S. Class 235, Subclass 379.

BACKGROUND ART

Automated banking machines are well known. A common type of automatedbanking machine used by consumers is an automated teller machine(“ATM”). ATMs enable customers to carry out banking transactions. Commonbanking transactions that may be carried out with ATMs include thedispensing of cash, the receipt of deposits, the transfer of fundsbetween accounts, the payment of bills and account balance inquiries.The type of banking transactions a customer can carry out are determinedby capabilities of the particular banking machine and the programming ofthe institution operating the machine. Other types of automated bankingmachines may allow customers to charge against accounts or to transferfunds. Other types of automated banking machines may print or dispenseitems of value such as coupons, tickets, wagering slips, vouchers,checks, food stamps, money orders, scrip or travelers checks. Forpurposes of this disclosure an ATM, an automated banking machine, or anautomated transaction machine shall encompass any device which carriesout transactions including transfers of value.

Many ATMs include modem processing systems with fast processors, largeamounts of memory, and large storage devices. Such processing systemsenable ATMs to display high resolution graphical user interfaces whichmay include audio visual presentations and other processor intensiveapplications. Although short interruptions in the operation of an ATMmay occur when the ATM is being serviced, in general ATMs are availablefor consumer use 24 hours a day, 7 days a week. Unfortunately consumersdo not generally use ATMs continuously 24 hours a day, 7 days a week.Even the most heavily used ATMs experience a significant number of idleperiods of non-consumer use. Although small amounts of processing powermay be used for maintaining the ATMs in an available state for futureconsumer uses, generally during such idle periods the processing systemsof ATMs remain significantly underutilized. Consequently there exists aneed for a system and method of providing productive uses for unusedprocessing power in ATMs.

ATMs typically generate income from transaction fees. Unfortunatelyduring off peak hours such as the early morning hours of a day,relatively few consumer transactions may be performed resulting inrelatively small amounts of income being generated. As a result therefurther exists a need for a system and method of generating additionalincome from ATMs during off peak hours.

DISCLOSURE OF INVENTION

It is an object of an exemplary form of the present invention to providean automated banking machine at which a user may conduct transactions.

It is a further object of an exemplary form of the present invention toprovide an automated banking machine that is more productive duringperiods of non-consumer use.

It is a further object of an exemplary form of the present invention toprovide an automated banking machine that is operative to generateincome during periods of non-consumer use.

It is a further object of an exemplary form of the present invention toprovide a system and method which provides additional uses for unusedprocessing power in ATMs. Further objects of exemplary forms of thepresent invention will be made apparent in the following Best Modes forCarrying Out Invention and the appended claims.

The foregoing objects may be accomplished in an exemplary embodiment byan automated banking machine or ATM that includes at least one outputdevice such as a display screen, and at least one input device such as atouch screen, function keys, keypad, a keyboard, card reader or othertype of input device. The machine may further include devices such as acash dispenser mechanism for sheets of currency, a receipt printermechanism, a depository mechanism and other transaction function devicesthat are used by the machine in carrying out transactions.

The ATM includes at least one computer processor. The computer processoris in operative connection with the output devices and the inputdevices, as well as with the cash dispenser mechanism, receipt printermechanism and other physical transaction function devices in the ATM.The computer processor includes software programs that are executabletherein.

In an exemplary embodiment, the software programs include a processingclient application. The processing client application is operative tocommunicate with a coordination server application located remotely fromthe ATM. In an exemplary embodiment the coordination server applicationis operative within a server computer processor of a financialtransaction processing system, which in this example may include a hostbanking system, or another networked server computing system inoperative connection with the ATM.

The exemplary embodiment of the processing client application isoperative to cause the computer processor of the ATM to perform tasksreceived by the processing client application from the coordinationserver application. The exemplary embodiment of the processing clientapplication may be operative to prevent the degradation of an ATM'sperformance while a consumer is using the ATM, by limiting theprocessing of a received task, to idle periods when a consumer is notusing the ATM and/or when the ATM is not performing transactionfunctions.

In the exemplary embodiment the coordination server application of theserver computer receives processing jobs from one or more job submittingentities. Such processing jobs may be divided into a plurality of tasksby the coordination server application and distributed among a pluralityof different ATMs. The jobs may be received from a computer system ornetwork address associated with the one or more job submitting entities.The jobs may also be manually inputted into the coordination serverapplication and/or retrieved from a portable storage medium. In otherexemplary embodiments, job submitting entities may include users whichmay submit a processing job to the coordination server applicationthrough operation of one of the ATMs in communication with thecoordination server application.

The exemplary embodiment of the coordination server application may beoperative to communicate with a plurality of ATMs connected througheither a private financial network or a public network such as theInternet. Responsive to the processing ability of each ATM and thecorresponding speed of each network connection to each ATM, theexemplary coordination server application may be operative toselectively divide one or more processing jobs among a plurality ofdifferent ATMs. As each ATM completes a received portion of the job or atask, the ATMs may be operative to forward the results of the tasks tothe coordination server application. The coordination server applicationassembles the results returned by the ATMs and continuously returnsadditional or other tasks to the ATMs to be processed during idleperiods.

In the exemplary embodiment, jobs may be received by the coordinationserver application from individuals, businesses, universities,governmental agencies, or other entities which require large amounts ofprocessing resources to process complex problems or other computerdefinable calculations or functions.

For example, a processing job may include the rendering of motionpicture images for an animated movie. Movies are often comprised of tensof thousands of individual images. The exemplary embodiment of thecoordination server application may be operative to send programminginstructions for rendering one or more different images of the movie toa plurality of different ATMs. During idle periods, the exemplary ATMmay be operative to perform ray tracing calculations or other imagerendering functions responsive to the programs which define each image.When an image has been completely rendered, an ATM may be operative toreturn a corresponding image file to the coordination serverapplication. The ATM may then continue processing additional images ormay perform other tasks received by the coordination server application.This process may continue until all of the images in the movie have beenrendered.

In this described exemplary embodiment, the coordination serverapplication may be operative to assemble the completed image files andforward them to the entity which submitted the processing job. In oneexemplary embodiment, the coordination server application may aggregateall or a portion of the tasks completed by the ATMs into a group beforeforwarding the group of the completed tasks to the job submittingentity. In other embodiments, the coordination server application mayperiodically or continuously return the results of individual tasks tothe job submitting entity as they are individually completed by theATMs. The coordination server application may be further operative tocalculate the total amount of processing time consumed by the ATMs toprocess the processing job and based on this amount, calculate theamount of fees to bill the entity which submitted the processing job.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a perspective view of an exemplary embodiment of an ATM thatis operative to process tasks associated with a processing job.

FIG. 2 is a schematic view of an exemplary embodiment of an ATMprocessing system.

FIG. 3 is a schematic view representative of exemplary embodiments of acoordination server application and a processing client.

FIG. 4 shows a listing of processing durations to complete a test taskby different models of ATMs.

FIG. 5 shows a listing of task results for a processing job for aplurality of different ATMs.

FIG. 6 is a schematic view of an exemplary embodiment of an ATMprocessing system that is operative to search for users of ATMs.

BEST MODES FOR CARRYING OUT INVENTION

Referring now to the drawings and particularly to FIG. 1, there is showntherein a perspective view of an exemplary automated banking machine orATM 10. The exemplary ATM 10 includes at least one output device such asa display device 12. The output device 12 is operative to provide aconsumer with a user interface 18 that includes a plurality of screensor other outputs including selectable options for operating the machine.The exemplary embodiment may further include other types of outputdevices such as speakers, or other types of devices that are capable ofoutputting visual, audible, or other sensory perceptible information.

The exemplary embodiment of the automated banking machine 10 includes aplurality of input devices such as function keys 14 and a keypad 16 aswell as a card reader 26. The exemplary embodiment of the ATM 10 mayfurther include or utilize other types of input devices, such as a touchscreen, microphone, or any other device that is operative to provide theATM with inputs representative of user instructions or information. Themachine may also include one or more biometric reader devices such as afingerprint scanner, an iris scanner, facial recognition device, handscanner, or any other biometric reading device which may be used to reada biometric input that can be used to identify a user.

The exemplary ATM 10 further includes a plurality of transactionfunction devices which may include for example a sheet or cash dispenser20, depository 22, a receipt printer 24 and other devices.

FIG. 2 shows a schematic view of an exemplary embodiment of an ATMprocessing system 50. The system may include a plurality of ATMs 52.These ATMs may include all or a portion of the features and devicesdescribed with reference to the ATM 10 of FIG. 1. The plurality of ATMs52 may be in operative connection with at least one server computingsystem 56 through a public or private network connection 58. In oneexemplary embodiment the network connection 58 and the server computingsystem 56 correspond to portions of a private financial transactionprocessing system such as a host banking system. However, in alternativeexemplary embodiments, the network connection 58 may correspond to apublic network such as the Internet and the server computing system 56may include a server in operative connection with the Internet.

The exemplary server computing system 56 may also be in operativeconnection with the computer systems of one or more job submittingentities 60 through a network connection 62. The network connection 62may also include a private network and/or a public network such as theInternet. The computer systems of the exemplary job submitting entities60 may include computers and/or other devices of individuals, companies,governmental agencies, universities or any other entity which isoperative to submit computer definable processing jobs to the servercomputing system 56.

The exemplary server computing system 56 includes a coordination serverapplication 54 operative therein. The coordination server application 54may be operative to communicate with each of the ATMs 52 and with one ormore job submitting entities 60. In one exemplary embodiment, thecoordination server application 54 may be operative to receive at leastone processing job 64 from the computer system of the job submittingentity 60. The coordination server application 54 may be furtheroperative to divide the processing job into a plurality of tasks 66which are distributed by the coordination server application to all or asubset of the ATMs 52. Examples of processing jobs may include raytracing calculations, database mining, cryptographic processes,unencrypting data, stock market analysis, DNA sequencing calculations,digital signal processing, finite elemental analysis and modeling,sub-atomic particle analysis, chemical property and reactioncalculations, analysis of images, analysis of biometric data, analysisof facial image data, analysis of data from monetary instruments,analysis of image data from check, analysis of data corresponding tocursive signatures or other handwriting, analysis of image data fromcurrency, or any other computer processing calculation, analyzation,function or program which can be subdivided into tasks for parallelprocessing by a plurality of ATMs.

The exemplary embodiments of the ATMs 52 may be operative to process thereceived tasks and return the results of the tasks 68 to thecoordination server application 54. The exemplary embodiment of thecoordination server application 54 may be operative to assemble the taskresults 68 and return the results of the processing job 70 to the jobsubmitting entity 60.

A processing job may be sent to the coordination server application fromthe job submitting entity as a complete group of individual tasks whichare divided among the ATMs after the job has been received. In additionthe processing jobs may be sent to the coordination server applicationfrom the job submitting entity as a continuous or periodic stream oftasks. The coordination server application may then begin dividing thetasks among the plurality of ATMs 52 before all of the tasks associatedwith the job have been received by the coordination server applicationfrom the job submitting entity.

Likewise, the job results 70 being returned to the job submitting entity60 from the coordination server application 54 may include all or aportion of the task results 68 received from the ATMs. Thus thecoordination server may wait until all of the task results 68 expectedhave been returned from the ATMs 54 before the job results 70 areassembled and returned to the job submitting entity 60 as one completedjob, or portions of the job results 70 may be periodically orcontinuously streamed from the coordination server application to thejob submitting entity as task results 68 are received from the ATMs 54.

FIG. 3 shows a schematic view of the exemplary server computing system56 and an exemplary ATM 10. The server computing system 56 includes atleast one server computer processor 55. As discussed previously, theserver computing system 56 includes a coordination server application54. The coordination server application 54 may be operative in the atleast one server computer processor 55. In addition the exemplary servercomputing system 56 includes at least one data store 80 in operativeconnection with the server computer processor 55. The coordinationserver application 54 may be operative to cause the server computerprocessor 55 to store and retrieve data in the data store 80.

The coordination server application 54 may be operative to store jobdata 82 in the data store 80 which describes each processing jobreceived by the job submitting entities. Further the coordination serverapplication 54 may be operative to store in the data store 80 task data86 in association with the job data 82 which describes tasks whichcomprise the processing job. In addition the coordination serverapplication may be operative to store in the data store 80, ATM data 84in association with the task data 86 which identifies which ATM has beensent the task to process. In one exemplary embodiment, each processingjob may be associated with a JobID number 88, each task may beassociated with a TaskID number 92, and each ATM may be associated withan ATMID number 90.

As shown in FIG. 3, each ATM 10 includes at least one computer processor100. The computer processor 100 may be in operative connection with atleast one output device 150 such as a display device. The computerprocessor may also be in operative connection with at least one inputdevice 152 such as a key pad, function keys, or touch screen. In theexemplary embodiment, the ATM 10 further includes a processing clientapplication 102 that may be operative in the computer processor 100. Theexemplary processing client application 102 may be operative tocommunicate with the coordination server application 54 for purposes ofreceiving tasks 66 and returning the task results 68. In addition theprocessing client application 102 may be operative to manage theprocessing of tasks by the computer processor 100 of the ATM 10.

In one exemplary embodiment the processing client application 102 may beoperative to communicate with consumer interface applications 104 whichare operative in the computer processor 100. Such consumer interfaceapplications 104 are responsible for enabling the ATM 10 to interactwith consumers and perform transaction functions. The consumer interfaceapplications 104 are in operative connection with a plurality oftransaction function devices 106 such as the previously described cashdispenser 20, depositor 22, and card reader 26.

In the exemplary embodiment, the processing client application 102 maybe responsive to the consumer interface applications 104 to control whentasks are processed by the computer processor 100. For example, when theATM 10 is being used by a consumer, the exemplary processing clientapplication 102 may be operative to detect this condition throughcommunication with the consumer interface applications 104 and as aresult stop, pause, or slow the amount of processing resources of thecomputer processor that are devoted to processing the task 66. When theATM is generally idle, the exemplary processing client application 102may be operative to detect this condition through communication with theconsumer interface applications 104 and as a result start, un-pause, orincrease processing resources of the computer processor 100 that aredevoted to processing the task.

In an exemplary embodiment, the computer processor 100 may be inoperative connection with a data store 108. The exemplary processingclient application 102 may be operative to store in data store 108 taskinformation 110 which describes tasks received by the coordinationserver application 54. As tasks are processed by the computer processor100, the exemplary client application 102 may be further operative tostore in data store 108 processing time duration information 112 inassociation with the task information 110. The duration information 112corresponds to the amount of processing time the computer processor 100has spent actively processing a task. For example, when the exemplaryATM is idle for 30 minutes of an hour, and that entire 30 minutes isdevoted to processing a task, the duration information 112 wouldassociate 30 minutes of processing time with the task information 110corresponding to the task being processed by the ATM.

In the exemplary embodiment, a task may require further processingapplications which correspond to the type of task being processed. Forexample a task corresponding to a digital signal processing calculationmay be associated with data which describes a signal and data whichdescribes calculations to be performed on the signal. However, toprocess the signal according to the calculations, the exemplary ATM mayrequire task specific processing components 120 such as server applets,functions libraries, subroutines, software objects, classes, scripts,DLLs, Java applets, Java beans, COM objects, ActiveXs, .Net objects,CORBA objects, or any other software component which can be used by theprocessing client application 102 to process the task. In an exemplaryembodiment, the processing client application 102 may be responsive tothe task data and other task instructions to cause one or more of aplurality of processing components 120 to process a task. Each of theexemplary processing components are responsive to the processing clientapplication 102 to start and pause the processing of tasks so that thetasks are generally only processed when the ATM is idle.

Examples of processing components 120 include image renderingapplications 122, digital signal processing applications 124, numericalprocessing applications 126, database mining applications 128, andfinite elemental analysis applications 132. In an exemplary embodiment,the processing components 120 may be pre-installed in a data store ofthe ATM. However, in alternative exemplary embodiments, received tasksfrom the coordination server application may include one or moreprocessing components that are operative to process the task. Forexample, a digital signal processing task may include both signal datato be processed and a custom processing component or application 130that may be operative to execute in the computer processor responsive tothe processing client application 102. The exemplary custom processingcomponent 130 may be operative to process the signal data or other dataassociated with the task or related tasks which are received by the ATM10 from the coordination server application 54.

In the exemplary embodiment the processing components 120 may includeobject code or libraries which are operative to execute in the computerprocessor 100 natively. In further exemplary embodiments, the processingcomponents 130 may include interpreted code such as Java® applets orJava beans which are operative to run within another application such asa Java Virtual Machine. In other exemplary embodiments, the processingcomponents may be comprised of a common intermediate language (CIL) suchas a .Net application object which may be just-in-time (JIT) compiled atthe ATM prior to executing in the computer processor of the ATM. Infurther exemplary embodiments, the tasks may include processingcomponents which are self contained and are not operative to processexternal data. For example, a task to render an individual clip from amovie may be comprised of a processing component 120 that includescompiled code for performing ray tracing calculations which define theimage. Any data which describes the locations of objects and lightsources for the image, may be encapsulated within the processingcomponent.

To prevent the spread of malicious viruses and worms in ATMs, theexemplary processing components may be digitally signed and beassociated with digital certificates. The digital signature and digitalcertificates may be used by the ATM to validate that the processingcomponents originate from a trusted source of processing components.Also, the ATM may be operative to execute the processing components in asecure runtime environment such as a virtual machine or sandbox. Such asecure runtime environment may include sufficient security to prevent amalicious processing client from accessing transaction functions devicessuch as a cash dispenser.

In the exemplary embodiment, as tasks are completed, the processingclient application 102 may be operative to send the task results 68 tothe coordination server application 54 and receive additional tasks forprocessing by the computer processor 100. The processing clientapplication 102 may be further operative to forward to the coordinationserver application the processing duration 112 associated with theprocessing of a task. When all or a portion of the tasks have beencompleted, the exemplary coordination server application may beoperative to forward the job results to the job submitting entity.

In the exemplary embodiment, the coordination server application 54 maybe operative to cause fees to be assessed to a job submitting entity forthe amount of ATM processing power time used to process a processing job64. The coordination server application may be operative to calculate atotal of the processing durations 94 associated with all of the tasks 86of a processing job. This total amount of processing time for aprocessing job may then be billed to the entity submitting the task.

For example, the exemplary system may be accessed by a job submittingentity such as a movie production company to render the individual movieframes of an animated film. In this described embodiment, the processingjob corresponds to the rendering of the movie, and the individual taskscorrespond to one or more individual frames of the movie. If ahypothetical average processing time for each frame of the movie by ATMsis one hour, then a 90 minute animated film comprised of 162,000 imageswould require 162,000 ATM hours to render. If the coordination serverapplication is in operative connection with 10,000 ATMs which are idle75% of the time, the system could render the movie in 21.6 hours(1/0.75*162,000/10,000). The job submitting entity, or in this case themovie production company, could be charged a processing fee based on thetotal number of ATM hours used to process the job (i.e. the 162,000 ATMhours). In exemplary embodiments such a processing fee may be based on anegotiated price per ATM hour.

In exemplary embodiments the system may charge fees based on a flat rateof monetary value per an amount of processing time used on a processingjob. In addition, exemplary embodiments of the system may charge feesbased on the number of ATMs devoted to a processing job. For example thefee rate for using 10,000 ATMs on a processing job may be higher orlower then the fee rate for using 100 ATMs on a processing job. Also,the fee rate for using slower model ATMs for a processing job may bedifferent than the fee rate for using faster ATMs on a processing job.In the exemplary embodiment, the coordination server application mayfurther be operative to calculate the fees for processing a jobsubmitted by a job submitting entity.

ATMs being used to process a single job may not all have equivalentprocessing power. For example older model ATMs may be relatively slow atprocessing tasks compared to new model ATMs with modem computerprocessors. If all ATM hours are treated equal, a given job would takemore ATM hours to complete using slower ATMs, than faster ATMs. As jobsubmitting entities may not want to pay higher processing fees whenportions of a job are processed by slower ATMs, the exemplarycoordination server application or other server software with access tothe duration data for task results, may be operative to normalize theduration data responsive to the relative processing speed of the ATMs.

For example, if a hypothetical slow ATM is operative to complete a giventask in two hours and a hypothetical fast ATM is operative to completethe same given task in half an hour, the exemplary system may beoperative to normalize the slower processing duration time data and/orthe faster processing duration time data relative to a selectedperformance baseline. The duration times for slower ATMs would benormalized downward based on the selected performance baseline andduration times for faster ATMs would be normalized upward based on theselected performance baseline. For example, if one hour is selected as aperformance baseline for the same given task, duration times for theslower ATMs could be halved and duration times for the faster ATMs couldbe doubled to produce normalized processing duration times for bothtypes of ATMS. The normalized duration times may then be summed todetermine a normalized number of ATM hours to complete the job. Theprocessing fee charged to the processing fee entity may then be based onthe total normalized number of ATM hours rather than the total of actualATM hours to complete the job.

As the relative difference between the processing speed of differentmodels or types of ATM systems may depend on the types of processingtasks, the exemplary system may be operative to sample the differentrelative processing speeds of different models or types of ATMs usingdesignated sample tasks from the job. For example, if a job is comprisedof one million tasks, the exemplary coordination server application mayallocate a small subset of test tasks selected from the one milliontasks to be given to a subset of all of the ATMs. The subset of ATMsselected may include ATMs that represent the different models or typesof ATMs that will be used to process the entire job. The duration timesto complete the test tasks for each of the different models or types ofATMs may then be compared to determine coefficients, factors or othernormalizing data which may be used to normalize the durations of thetask results submitted for similar models or types of ATMs. For example,each individual duration time may be normalized first and then summed todetermine a normalized amount of ATM hours to base a processing fee forthe job. In other embodiments, the actual duration times of tasks foreach model of ATM may be separately totaled for a job. When the job iscompleted, these separate duration totals for each ATM model may benormalized responsive to the normalizing data for each model of ATM. Thenormalized duration totals for each type of ATM may then be summed todetermine a normalized amount of ATM hours to base a processing fee forthe job.

FIGS. 4 and 5 show an example of normalized data for a hypothetical jobwhich may be determined by the coordination server application 54 andstored in the data store 80. As shown in FIG. 5, the hypothetical job iscomprised of seven tasks 220. The exemplary coordination serverapplication may be operative to select a subset of the tasks for use astest tasks to determine the relative processing capabilities such asprocessing speeds for models of ATMs that will be used to process thejob. In this example, TaskID 6 is chosen and is communicated to theprocessing client applications of five different models of ATMs whichwill be used to process the job. FIG. 4 shows the duration times 200 tocomplete TaskID 6 for each of the five ATM models (A-E) 202. In thisexample the normalizing baseline is selected to correspond to a durationequal to the fastest time submitted by the different models of ATMs. Inthis case the duration time of 0.5 hours for ATM model C is selected forthe baseline. However, it is to be understood that the baseline chosento normalize duration times may be a different slower or faster timeduration. For example, with other jobs the baseline may correspond to:the duration time for the slowest ATM (ex. 4 hrs for ATM model E); theaverage or mean duration time for the different models; or some otherselected duration time.

Based on a selected baseline of 0.5 hours, FIG. 4 shows normalizing datasuch as normalizing factors 204 that the coordination server applicationmay determine responsive to the selected baseline duration and thesample duration time results for the test task. Such normalizing factorsmay be used by the coordination server application to normalize theduration times returned by ATMs to process the tasks for the job.

FIG. 5 shows an example listing 218 of hypothetical job results for theseven tasks 220 that comprise the job. In this example the coordinationserver application divided the task among seven different ATMs 224. Thelisting includes the actual duration times 222 reported by the ATMs 224to complete their designated task. The listing also includes thecorresponding ATM models 226 for the ATMs 224.

In this example, the exemplary coordination server application may beoperative to normalize the actual duration times 222 responsive to thenormalizing factors 204 determined previously and shown in FIG. 4. Inthis example the normalized durations 228 are calculated by multiplyingthe actual duration times 222 by the normalizing factor 204 whichcorresponds to the matching model of ATM that processed the task. Theexemplary coordination server application may sum the normalizeddurations 228 to determine the normalized number of ATM hours 230 ittook to complete the job. Processing fees may then be based on thenormalized total of ATM hours 230 to complete the job rather than theactual total of ATM hours 232 to complete the job. Without normalizingthe ATM hours, job submitting entities may demand that only the fastestmodel ATMs (such as ATM model C) be used. By normalizing the processingdurations, the slower ATMs (such as ATM model E) may still be utilizedto process portions of the jobs without inflating the processing feescharged to the job submitting entity.

As discussed previously, in other embodiments, the coordination serverapplication may determine separate totals of the actual duration times222 for each of the five models of ATMs used to process the job. Suchduration time totals for each ATM model may then be normalizedresponsive to the normalizing factors 204 prior to being summed fordetermining the total normalized ATM hours for the job

In other embodiments, other methods of compensating for the differencesin processing ability between different models or types of ATMs may beused. For example, different processing fee rates for each type of modelmay be used to calculate the total processing fee. Such differentprocessing fee rates may be calculated based on the sample task durationtimes 200 and/or the normalizing data 204 determined for the differentATM models 202. For example the processing fee rate for the use of modelB ATMs may be set at half the processing fee rate for model C ATMsbecause the processing speed of model B ATMs is determined by thecoordination server application to be half the speed of the model CATMs. The different processing fee rates may than be used to calculateseparate processing fees for each model of ATM used to process portionsof the job. As discussed previously, the exemplary coordination serverapplication may derive separate duration time totals for each model ofATM. These separate duration time totals for each ATM model may then bemultiplied by their respective processing fee rates to determineprocessing fees for each portion of the job processed by the variousmodels of ATMs.

Before submitting a processing job, job submitting entities may wish tohave an estimate of the number of ATM hours and/or processing fees thatmay be associated with the processing of a job. As the costs associatedwith all the individual tasks that make up a job may not be readilycalculated prior to processing a job, the exemplary coordination serverapplication 54 may be operative to generate estimates of the amount ofprocessing time and fees that will be required to complete a submittedprocessing job.

As discussed previously with respect to calculating the relative speedof different models of ATMs, the exemplary coordination serverapplication may be operative to submit to one or more ATMs, a smallsubset of one or more test tasks selected from the many tasks thatcomprise the processing job. These test tasks may also be used toestimate an amount of processing time or ATM hours required to performthe job. Based on this estimate of ATM hours, the exemplary coordinationserver application may be operative to estimate the total amount ofprocessing time and costs required to complete the processing job. Thisestimate may be forwarded to the submitting entity by the coordinationserver application 54 for evaluation prior to purchasing access to theexemplary system for processing a proposed job.

In further exemplary embodiments, the coordination server applicationmay be operative to select which ATMs to send the tasks based on thebandwidth requirements of the tasks. For example, tasks which arecomprised of a large number of bytes or produce task results with alarge number of bytes may only be allocated to those ATMs which have arelatively fast network connection to the coordination serverapplication such as a DSL, T1, or high bandwidth leased connection.Tasks associated with a relatively small number of bytes which must betransferred between the ATM and the coordination server application, maybe allocated to those ATMs which have a relatively slower networkconnection such as a dial-up phone line. The coordination serverapplication may also charge different processing fee rates for differentsets of ATMs based on the relative speed of the network connection ofthe sets of ATM.

It is to be understood that exemplary embodiments of the system may beused to process other types of jobs that may be divided into a pluralityof tasks. Other examples of processing jobs may include processing aspectrum of measured signal data, where each task includes the numericalprocessing of individual segments of band width of the signal data.Other processing jobs may include calculating data using a specifiedfunction, wherein each task includes a different set of arguments to thefunction. Further, other jobs may involve finite elemental analysiscalculations and modeling with each task corresponding to different setsof constraints. Other exemplary embodiments may include cryptographycalculations such as unencrypting data, where each tasks corresponds toone or more different keys which are used to attempt to decipher thedata.

In further exemplary embodiments, the coordination server applicationmay be operative to generate additional tasks based on the results ofprocessed tasks. For example a job may include a multi-step processcalculation. As a result a first set of ATMs may be given tasks forprocessing a first portion of the calculation. The results of thosetasks may be organized into new tasks by the coordination serverapplication and submitted back to the first set of ATMs or to a secondset of ATMs to calculate a second portion of the calculations. Theexemplary coordination server application may be operative to managemultiple iterative and/or recursive calculations of a processing job byrouting tasks and the results of tasks among a plurality of ATMs forprocessing.

In further exemplary embodiments, the ATMs may be operative to forwardtasks and results of tasks to other ATMs through a peer to peer networkconfiguration. ATMs may spawn off one or more tasks to one or more otherATMs directly rather then requiring the coordination server applicationto manage the distribution of all tasks to ATMs. The ATMs may also beoperative to pass messages, task results, and/or processing componentsbetween themselves to facilitate processing tasks.

In further exemplary embodiments, individual ATMs may be operative toreceive processing jobs from users through the input devices of the ATMterminals. The processing jobs may be forwarded to the coordinationserver application by the ATM. The coordination server application maythen divide the job into a plurality of tasks and distribute those tasksto a plurality of ATMs to process. As discussed preciously the resultsof the tasks may be returned to the coordination server application andforwarded to an e-mail address or other network accessible addresssupplied by the user that originally submitted the job through an ATM.

In addition the coordination server application may store the results ina data store. When the user wants to review the job results he mayreturn to the original or another ATM. The ATM may enable the user tosubmit a command or request message through operation of the ATM whichis operative to cause the job results to be retrieved from the datastore and be forwarded to the ATM by the coordination serverapplication. The ATM may then be operative to output the job results forthe user through the display device of the ATM or a printer. Inaddition, as schematically shown in FIG. 3, the ATM may include aseparate portable storage medium drive 154 that is operative to readand/or write information to a portable storage medium. In otherexemplary embodiments, the card reader 26 may function as a portablestorage medium drive that is capable of reading and writing informationrelated to processing jobs from a smart card or other memory card whichis operate to store information. Such card reader may be operative toread financial account information from a financial account card,retrieve processing jobs from the smart card and save processing jobresults back to the smart card.

In other exemplary embodiments the ATM may include other types ofportable storage medium drives 154 such as an Iomega Jaz® drive; magnetooptical drives such as an Iomega Zip® drive; flash memory drives forwriting to flash memory devices such as CompactFlash and Sony MemoryStick®; PC Card Interfaces; CD drives, DVD drives; Mini-CD drives; anddigital tape drives. The exemplary embodiment of the ATM may alsoinclude a wired or wireless communication port 156 that is operative tocommunication with a portable computing device such as a mobile phone,notebook computer, or a PDA. The ATM through operation of thecommunication port may be operative to receive processing jobs and sendthe results of the processing jobs to the portable computing devices.

In other embodiments, the user may access any of the plurality of ATMsin operative connection with the coordination server application toretrieve the job results from the coordination server application. In afurther exemplary embodiment, the coordination server application may beoperative to provide access to the job results through an HTTP serversuch as an Internet web server which is in operative connection with thecoordination server application and/or data store. Users may than loginto the web server to retrieve the processing job results stored in thedata store by the coordination server application.

The processing fees used to pay for processing the job may be collectedfrom the user through operation of the ATM. For example, the ATM mayprompt the user to insert a credit card, debit card, checking accountcard, or other financial account card into a card reader of the ATM. TheATM may cause the card reader to retrieve the necessary accountinformation from the card for purposes of assessing processing fees tothe financial accounts associated with the cards. In an exemplaryembodiment, the ATM may be operative to assess processing fees to afinancial account of the user through communication with a financialtransaction processing computer or system which is operative to carryout financial transfers and authorizations.

The processing fees may be charged either before or after the processingjob has been completed. As discussed previously, the processing fees maybe determined prior to the completion of the job, by processing portionsof the job to determine an estimate of the amount of processing time theentire job will require. Such processing fees charged to the user'sfinancial account may then be based on the estimate for the processingtime to complete the job. In other exemplary embodiments, the processingfees may be based on a flat rate or other rate responsive to the type ofthe processing job and/or the processing parameters selected by theuser. For example ATMs may be operative to output through a displaydevice a menu which lists a plurality of different types of processingjobs. One or more of the different types of processing jobs may then beselected by the user through operation of the input devices of the ATM.Parameters for performing the selected type of processing job may thenbe inputted through the input devices of the ATM and/or be retrievedfrom a portable storage medium or a portable computing device of theuser. The fees charged to the user's financial account may be based onthe selected type of processing job and/or the inputted parameters usedin processing the job.

For example, the user may wish to perform data mining on one or moredatabases. An exemplary embodiment of the ATM may be operative to outputone or more menu screens that include a listing of different databasesthat are available for data mining through the ATM. Databases forexample, may include census data, genome sequencing data, financialdata, or any other large database of information which users may finduseful for data mining processing.

The ATM may further provide one or more screens that prompt the user toprovide parameters to be used in performing the data mining processingin the selected database. Examples of parameters used in data miningprocessing and other processing jobs may include individual parameterssuch as date ranges and geographical regions. The processing feescharged to the user's financial account by the ATM may be based on theparticular database selected and/or the type of parameters selected. Forexample, processing fees involving database mining through a database ofcensus data may cost less for a parameter associated with an individualstate compared to a parameter associated with all of the United States.

To provide more complex parameters involved with the data mining, theATM may be operative to retrieve the parameters from a portable storagemedium or portable computing device of a user. Examples of other morecomplex parameters may include expert system evaluation trees,statistical algorithms, or other data, which may be used to analyze orprocess data in the selected database. In other exemplary embodiments,the ATM may be operative to retrieve from a portable storage medium ofthe user, a plurality of different types of processing components,databases, images, or other objects may be used by the coordinationserver application, and/or ATMs to process the requested job.

Examples of other processing jobs that may be initiated through an ATMor through the coordination server application, may include searches forindividuals using the ATMs. For example, as shown in FIG. 1, an ATM mayinclude a camera 15 that is operative to capture image data of theperson operating the ATM. The image data captured by the camera of theATM may include images in the form of video frames and individual imagefiles. The captured ATM image data may be processed by an exemplaryembodiment of the system for use with identifying or finding people.

As shown in FIG. 6, an exemplary server 300 is in operative connectionwith a plurality of ATMs 302. The server 300 may include the previouslydescribed coordination server application 306, and a data store 308.Each of the ATMs 302 may include a camera 304 which is operative tocapture image data of the users operating the ATMs. In an exemplaryembodiment the ATMs 302 may be operative to send one or more capturedATM image files or video frames of the user to the coordination serverapplication 306 or some other server application of the server 300 forstorage in the data store. Such ATM image data may be stored inassociation with transaction data associated with the operation of theATM by the user. Such transaction data may include the location of theATM where the image data was captured and the date and time the imagedata was captured. In addition the transaction data may include theaccount numbers associated with the card or cards used to access themachine and the types of transactions performed at the ATM. Thetransaction data may further include information about the financialaccounts associated with the account numbers, such as the names andaddresses of the account holders.

Job submitting entities such as law enforcement individuals or otherindividuals may submit processing jobs 312, 314 through one of the ATMs302 or through a public network such as the Internet 310 to thecoordination server application 306. Such processing jobs may includeone or more images of people to search for from among the peoplepictured in the captured ATM images. Searches may involve comparing thereceived search image data showing a known or suspected criminal orterrorist to the image data captured by the ATMs. The tasks involvedwith the processing job may correspond to performing imaging processingfunctions on the ATM image data which are operative to quantifycharacteristics of the users shown in the ATM image data.

In an exemplary embodiment, the coordination server application 306 maydivide the image processing of the ATM images data among the pluralityof ATMs 304. As a result each ATM would receive copies of one or more ofthe previously captured ATM image files from the data store 308 and acopy of one or more search image files from the submitted processingjob. Each individual ATM may then perform image analysis calculations onthe ATM image data and search image data to determine if the individualsshown in the ATM and search image data are similar. Task results 316returned to the coordination server application 306 by the ATMs 302 mayinclude data which indicates a level of correlation or similaritybetween the person shown in the ATM image data and the person shown inthe search image data. The results of the precessing job may include alisting of matching image files captured by the ATMs and portions of theassociated transaction data such as the date and time the image wascaptured, the location of the ATM, the financial accounts accessed, andthe account holder name associated with the financial accounts accessed.

In another exemplary embodiment, the ATMs 302 may be operative toprocess the ATM image data prior to forwarding the ATM image data to thecoordination server application 306 for storage in the data store 308.Such processing may include determining identity data from the ATM imagedata. The ATM identity data may quantify identifying features of theperson depicted in the ATM image data such as hair color, facial hair,baldness, eye color, skin color, height, scars, and facial measurements.Facial measurements, for example, may include measurements related tofeatures of the individuals face such as the relative positions anddistances between the eyes, nose, mouth, neck, ears, and hairline of theindividual. These measurements or other identifying data determined fromthe image data may be submitted to the coordination server application306 for storage in the data store 308 along with the associated ATMimage data and the associated transaction data.

When a processing job is received related to searching through the ATMimage data for a particular person, the coordination server application306 may search through the data store 308 and select only those ATMimage files and transaction data from the data store 308 that areassociated with similar identity data as the person being searched for.Because the ATM image data has been previously processed, thecoordination server application can quickly select one or more recordsfrom the data store 308 which include ATM identity data with featuresand measurements that correspond to the features and measurements of theidentity data of the person being searched for.

For example, a job submitting entity such as a police officer may submita processing job that corresponds to a search for a person. Theprocessing job may include search image data such as an image file ofthe person which is uploaded to the coordination server application 306.The coordination server may then process the uploaded image of theperson to determine corresponding search identity data associated withthe person being searched for. The search identity data from the searchimage data may then be compared to the plurality of records in the datastore which include ATM identity data corresponding to users of ATMs.Matching ATM image data and associated transaction data may then bereturned to the police officer or other job submitting entity forfurther analysis.

In further exemplary embodiments, the coordination server may acceptsearch identity data directly from the job submitting entity whichcorresponds to the person being searched for. In other exemplaryembodiments, the coordination server may accept both search image dataand additional search identity data corresponding to the person. Forexample the submitted search image data may include a black and whiteimage file. The job submitting entity may also submit search identitydata with the search image data which describes features that can not bedetermined from the black and white image such as eye and hair color ofthe person shown in the black and white image file.

In one exemplary embodiment the search image data may be received by thecoordination server application from a remote client computer 318. Sucha remote client computer may be in communication with the coordinationserver application 306 through an Internet web server or through e-mailfor example. In another exemplary embodiment, the search image data maybe uploaded to the coordination server application through operation ofone of the ATMs 302. As discussed previously, an exemplary ATM mayinclude a portable storage medium drive. The ATM may retrieve searchimage data such as a search image file from a portable medium placed inoperative connection with the portable storage medium drive. In otherexemplary embodiments the ATM may retrieve the search image file from aportable computing device placed in operative connection with the ATM bythe user. In other exemplary embodiments, the ATM may include a scanningdevice which is capable of capturing a search image file from a physicalphotograph.

When the coordination server application has completed searching thedata store 308 of captured ATM images which match the submitted searchimage, the job submitting entity may send a request message to thecoordination server which is representative of a request to return theresults of the search. In response, the coordination server may returnsearch results data which includes the results of the search. Suchresults may includes information about the determinations made by thecoordination server when performing the search. Such determinations mayinclude a listing of those captured images which most closely match thesearch image. The determinations may further include a ranking of thematching ATM image data which is based on the relative similaritybetween the ATM image data and the search image data. Such a ranking forexample may be based on the percentage of identity data of the capturedimages which corresponds to the search identity data of the searchimage. In addition the search results data may include one or more ATMimage files or video frames and at least portions of the transactiondata associated with the ATM image data.

In an exemplary embodiment, the search results data may be retrievedfrom the coordination server by accessing one of the ATMs 302. Exemplaryembodiments of the ATMs may enable a user to send a request message tothe coordination server which corresponds to a request to send thesearch result data to the requesting ATM. In an exemplary embodiment,the ATM may output the images and associated transaction data through anoutput device of the ATM such as a printer or display screen. Also theexemplary embodiment of the ATM may save the search results to aportable storage medium or to a portable computing device of the user.

In other exemplary embodiments, search results data may be sent by thecoordination server application to an e-mail address or other networkaccessible address specified by the user when the search image data wassubmitted to the coordination server. In further exemplary embodiments,the coordination server may be in operative connection with an HTTPserver which is operative to send the search results as part of a webpage to a browser of a remote computer.

In an exemplary embodiment, the ATM image data may be processed by theATMs to determine ATM identity data prior to uploading to thecoordination server. In other exemplary embodiments the coordinationserver may process the ATM image data to determine the ATM identitydata. In further exemplary embodiments, the processing of the ATM imagedata may be performed by both the coordination server and the ATM. Inaddition, in further exemplary embodiments, the coordination server mayallocate to a plurality of the ATMs, tasks which include ATM image datato process. The task results returned to the coordination server mayinclude ATM identity data determined from the captured ATM images.

In this described exemplary embodiment, the search image data does notcorrespond to a user who is authorized to perform transaction functionsat an ATM. In addition the search image data does not originate from acamera of an ATM and does not correspond to a person who is beingsearched for from among ATM image data to determine if the person isauthorized to perform transaction functions at an ATM. Also,authorizations of transactions at ATMs are not performed responsive tomatches between captured ATM image data of the user and search imagedata. Rather transactions by a user at exemplary embodiments of the ATMsare authorized without reference to the search image data. Suchtransactions for example may be authorized by the user entering a PINnumber or a biometric data which is validated by the systemindependently of the search image data. In the exemplary embodiment, thesearch image data is not used by the system to validate or authorizetransactions at ATMs by users.

In a further exemplary embodiment, a processing job may correspond to anongoing search for one or more particular individuals that use an ATM inthe future. For example, a processing job may include search image datasuch as an image file and/or identifying features of a person to searchfor. However rather than or in addition to searching through apre-existing data store of ATM image data, the coordination serverapplication may continually monitor all newly captured ATM image dataand/or ATM identity data determined from the newly captured ATM imagedata for matches with the person being searched for as part of theprocessing job. Thus for example, if a governmental entity such as a lawenforcement entity is searching for a suspected terrorist or a missingperson, the search image data showing the person and/or search identitydata associated with the person may be continually compared to all or asubset of the newly captured ATM image data or determined ATM identitydata. When a match is found between ATM image data of a user operatingan ATM and the search image data of the person being searched for, theexemplary coordination server application may be operative to send thesearch results data in the form of an alert or warning message to anaddress associated with the search. Such an address for example may bean e-mail message or other communication address of the entity thatsubmitted the search. The alert message may include captured ATM imagefiles or video and the date, time and location of the ATM where the ATMimage was captured. The alert message may further include the name ofthe account holder or other transaction data associated with thefinancial account being used by the person at the ATM.

In exemplary embodiments, the processing job may include parameters tobe used when performing the search of ATM image data. Such parametersmay limit the search to ATM image data from a specific geographicallocation and/or time period. Such parameters may further specify whichof a plurality of determined ATM identify data to limit the search. Forexample, ATM image data may be processed to determine ATM identity datasuch as hair color, facial hair, baldness, eye color, skin color,height, scars, and facial measurements. The parameters included in aprocessing job may limit which identity features are evaluated or mayassign weighing factors as to which identity features are more or lessimportant when calculating whether ATM image data should be considered amatch by the system.

In addition to performing image analysis on image data captured fromusers of ATMs, exemplary embodiments the system may further processother types of images or other types of data captured from ATMs. Forexample, the depository mechanisms of ATMs may include cameras or othersensors which are operative to capture image data or other measurabledata from items deposited into the ATM. Such items may include monetaryinstruments such as checks, currency, coins, or other items which aredeposited into an ATM. The ATM which receives the deposited item mayitself process the captured image data or other measurable data by theATM. In addition the ATM may uploaded the image data or other measurabledata to a remote server for processing by the remote server or otherATMs.

The processes performed on such image data or other measurable data mayinclude handwriting analysis such as cursive signature analysis of thesignatures written on checks deposited with the ATM. Processes may alsoinclude analysis of deposited monetary instruments such as cash forindications whether the item is a forgery.

As discussed previously, such processes may be performed while the ATMis generally idle and is not being used to perform consumer transactionfunctions. The results of the processing may then be uploaded to aremote server application such as the previously described coordinationserver application for storage in one or more data stores and forrouting to other computer systems.

Thus the new ATM processing system and method achieves at least one ofthe above stated objectives, eliminates difficulties encountered in theuse of prior devices and systems, solves problems and attains thedesirable results described herein.

In the foregoing description certain terms have been used for brevity,clarity and understanding, however no unnecessary limitations are to beimplied therefrom because such terms are used for descriptive purposesand are intended to be broadly construed. Moreover, the descriptions andillustrations herein are by way of examples and the invention is notlimited to the exact details shown and described.

In the following claims any feature described as a means for performinga function shall be construed as encompassing any means known to thoseskilled in the art to be capable of performing the recited function, andshall not be limited to the features and structures shown herein or mereequivalents thereof. The description of the exemplary embodimentincluded in the Abstract included herewith shall not be deemed to limitthe invention to features described therein.

Having described the features, discoveries and principles of theinvention, the manner in which it is constructed and operated, and theadvantages and useful results attained; the new and useful structures,devices, elements, arrangements, parts, combinations, systems,equipment, operations, methods and relationships are set forth in theappended claims.

1. A method comprising: (a) receiving a processing job through operationof at least one computer, wherein the processing job includes searchimage data related to a person, wherein the processing job correspondsto searching for at least one user of an automated banking machine whichcorresponds to the person, wherein the automated banking machineincludes a card reader and is operative to carry out financialtransactions for users of the automated banking machine; (b) capturingfirst image data corresponding to a first user operating a firstautomated banking machine through operation of a camera, wherein thefirst image data is associated with first transaction data correspondingto operation of the first automated banking machine by the first user;(c) authorizing through operation of the at least one computer at leastone financial transaction by the first user at the first automatedbanking machine independent of the search image data, wherein the firsttransaction data corresponds to the at least one financial transaction;(d) comparing through operation of the at least one computer, the firstimage data and the search image data; (e) determining through operationof the at least one computer that the user depicted in the first imagedata is visually similar to the person depicted in the search imagedata; and (f) generating search results data through operation of the atleast one computer responsive to the determination in step (e), whereinthe search results data includes at least a portion of the firsttransaction data.
 2. The method according to claim 1, wherein in step(f) the search results data further includes at least a portion of thefirst image data.
 3. The method according to claim 2, wherein in step(f) the search results data are generated through operation of at leastone server, and further comprising: (g) operating the at least oneserver to provide access to the search results data by at least onefurther computer located remotely from the at least one server.
 4. Themethod according to claim 3, wherein in step (g) the at least one serverincludes an HTTP server that is operative to transfer the search resultsdata to the at least one further computer.
 5. The method according toclaim 2, wherein the at least one computer includes a server, andwherein in step (f) the search results data are generated by the server,wherein further comprising: (g) retrieving the search results data fromthe server through operation of a second automated banking machine. 6.The method according to claim 5, wherein further comprising: (h)outputting indicia corresponding to the search results data through anoutput device of the second automated banking machine.
 7. The methodaccording to claim 5, and prior to step (f) further comprising: (h)capturing second image data corresponding to a second user operating thesecond automated banking machine through operation of a camera, whereinthe second image data is associated with second transaction datacorresponding to the operation of the second automated banking machineby the second user; (i) comparing through operation of the at least onecomputer the second image data and the search image data; (j)determining through operation of the at least one computer that the userdepicted in the second image data is visually similar to the persondepicted in the search image data; and wherein in step (h) the searchresults data further includes at least a portion of the secondtransaction data.
 8. The method according to claim 7, wherein prior tostep (f) further comprising: (k) operating the at least one computer toassign a first ranking to the first image data and a second ranking tothe second image data responsive to the relative similarities betweenthe search image data and the first and second image data; wherein instep (f) the search results data further includes the first and secondrankings, and the first image data and the second image data are listedin an order that corresponds to the first and second rankings.
 9. Themethod according to claim 1, wherein in step (f) the portion of thefirst transaction data includes at least one of: informationrepresentative of a date and a time of the operation of the firstautomated banking machine by the first user; information representativeof at least one financial account associated with the operation of thefirst automated banking machine by the first user; informationcorresponding to at least one account holder name associated with the atleast one financial account; and information representative of alocation of the first automated banking machine.
 10. The methodaccording to claim 1, wherein step (d) is carried out through operationof at least one computer in the first automated banking machine, whereinthe first automated banking machine includes a cash dispenser.
 11. Amethod comprising: (a) acquiring through operation of at least onecomputer from a plurality of automated banking machines, wherein eachautomated banking machine includes a card reader and is operative tocarry out financial transactions, image data depicting users using theplurality of automated banking machines, wherein the image data for eachuser depicted in the image data is associated with transaction datacorresponding to the use of the respective automated banking machine bythe respective user, wherein at least one of the automated bankingmachines includes a cash dispenser; (b) receiving through operation ofthe at least one computer search image data depicting a person beingsearched for, wherein the search image data did not originate from acamera associated with any of the plurality of automated bankingmachines; (c) identifying through operation of the at least one computerat least one user depicted in the image data that is visually similar tothe person depicted in the search image data; and (d) generating searchresults data through operation of the at least one computer whichincludes both the image data and at least a portion of the transactiondata associated with at least one user identified in step (c).
 12. Themethod according to claim 11, and further comprising: (e) processing theimage data through operation of the at least one computer to determineuser identity data associated with each of the users; (f) storingthrough operation of at least one computer in at least one data storethe image data, the user identity data, and the transaction data; (g)processing through operation of the at least one computer the searchimage data to determine search identity data associated with the personbeing searched for; and wherein step (c) includes searching the at leastone data store for at least one user for which at least a portion of theuser identity data associated with the at least one user corresponds tothe search identity data.
 13. The method according to claim 12, andfurther comprising: (h) prior to step (f), transferring the image datafrom each of the plurality of automated banking machines, to at leastone server, wherein in step (f) the at least one server is operative tostore the image data, the user identity data, and the transaction datain the at least one data store.
 14. The method according to claim 11,wherein the at least one computer operative to carry out step (c) isincluded in at least one of the automated banking machines.